English

Simplification and Improvement of MMS Approximation

Computer Science and Game Theory 2023-07-25 v2

Abstract

We consider the problem of fairly allocating a set of indivisible goods among nn agents with additive valuations, using the popular fairness notion of maximin share (MMS). Since MMS allocations do not always exist, a series of works provided existence and algorithms for approximate MMS allocations. The Garg-Taki algorithm gives the current best approximation factor of (34+112n)(\frac{3}{4} + \frac{1}{12n}). Most of these results are based on complicated analyses, especially those providing better than 2/32/3 factor. Moreover, since no tight example is known of the Garg-Taki algorithm, it is unclear if this is the best factor of this approach. In this paper, we significantly simplify the analysis of this algorithm and also improve the existence guarantee to a factor of (34+min(136,316n4))(\frac{3}{4} + \min(\frac{1}{36}, \frac{3}{16n-4})). For small nn, this provides a noticeable improvement. Furthermore, we present a tight example of this algorithm, showing that this may be the best factor one can hope for with the current techniques.

Keywords

Cite

@article{arxiv.2303.16788,
  title  = {Simplification and Improvement of MMS Approximation},
  author = {Hannaneh Akrami and Jugal Garg and Eklavya Sharma and Setareh Taki},
  journal= {arXiv preprint arXiv:2303.16788},
  year   = {2023}
}
R2 v1 2026-06-28T09:40:10.141Z